Browsing: Artificial Intelligence

The productivity gains from AI tools are undeniable. Development teams are shipping faster, marketing campaigns are launching quicker, and deliverables…

Large language models (LLMs) have shown potential for medical and health question answering across various health-related tests spanning different formats…

In the promising and rapidly evolving field of genetic analysis, the ability to accurately interpret whole genome sequencing data is…

MIT Department of Mathematics researchers David Roe ’06 and Andrew Sutherland ’90, PhD ’07 are among the inaugural recipients of…

UNSW engineers have made a significant advance in quantum computing: they created ‘quantum entangled states’ – where two separate particles…

OpenAI hasn’t released an open-weight language model since GPT-2 back in 2019. Six years later, they surprised everyone with two:…

Note: This post is an excerpt from the forthcoming book, Deep Learning and Scientific Computing with R torch. The chapter…

Every year, MIT Technology Review selects one individual whose work we admire to recognize as Innovator of the Year. For…

In the rush to get the most from AI tools, prompt engineering—the practice of writing clear, structured inputs that guide…

Experiments We tested SLED across multiple LLMs with varying configurations and scales. Due to its flexible nature, the SLED method…